Survey data is often presented in aggregated, depersonalized form, which can involve binning underlying data into quantile buckets; for example, rather than reporting underlying income, a survey might report income by decile. split_quantile can automatically produce this split using any data x and any number of splits type.

split_quantile(x = NULL, type = NULL)

## Arguments

x A vector of any type that can be ordered -- i.e. numeric or factor where factor levels are ordered. The number of buckets to split data into. For a median split, enter 2; for terciles, enter 3; for quartiles, enter 4; for quintiles, 5; for deciles, 10.

## Examples


# Divide this arbitrary data set in 3.
data_input <- rnorm(n = 100)
split_quantile(x = data_input, type = 3)#>   [1] 1 3 3 3 3 2 3 3 3 2 1 2 2 3 1 1 1 2 2 1 1 3 1 1 2 2 3 3 2 2 2 2 1 2 2 2 3
#>  [38] 1 1 1 1 1 3 1 3 1 1 2 3 3 3 3 1 2 3 1 3 3 3 1 1 1 1 1 2 3 3 2 3 3 1 3 1 2
#>  [75] 1 2 1 3 2 3 2 1 3 2 2 2 1 3 2 2 1 1 1 3 2 3 2 2 2 2
#> Levels: 1 2 3
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